Strategic planning is critical to the future success of any enterprise--an enterprise being any organization or business concern which produces products or renders services. The goal for a planning manager is to position the enterprise so that it can respond profitably to future market trends.
For example, a manager of a large industrial enterprise with a global market orientation, such as an aerospace engineering firm, might attempt to gather information on whether the world market for a particular engine part will be strong, weak, or non-existent, before making resource allocation decisions, such as leasing factories and equipment, or hiring employees for work. Perhaps the current product needs to be redesigned before it goes to the market. Perhaps a competitor has a new product that makes the current design obsolete, or perhaps the costs involved in re-tooling factories and retraining employees will be so expensive that the project should be dropped. Resolution of such decisions will affect the positioning of the enterprise in making capital investment and resource allocation decisions.
Generally, the resource allocation decisions made through the strategic planning process have a tremendous impact on the character and continued viability of the enterprise--so the stakes are high for the planning manager. Resource allocation decisions based on strategic planning analysis are typically made on a highly aggregated basis, and the time horizon for this planning, though arbitrary, typically ranges from three to ten years. If a planning manager's projections accurately anticipate the market trends, the enterprise will tend to thrive. Otherwise, it is likely to falter or even fail.
Planning managers spend much time and effort developing strategic resource allocation plans. Such a plan is a recommendation of the general direction an enterprise should take, containing an aggregate-level statement of resource allocation, and a statement of the assumptions underlying the plan. Those underlying assumptions are projections of conditions that the enterprise will most likely face. In planning, managers attempt to predict the future evolution of products, production processes, markets and other factors that will affect future production. Managers typically consider the forces that affect the making and marketing of a product, such as changes in the cost of raw materials to produce the product, the particular needs of large customers, the products offered by competitors, the need for product re-design, trends in component technology, trends in manufacturing process technology, changes in the employee skills needed, changes in manufacturing productivity (using measures such as manufacturing output per person, manufacturing output per manufacturing space or capital required per employee), inventory flow trends, as well as societal and governmental influences. The projections needed to make a resource allocation decision might include:
Projections pertaining to the size, location or description of the market for goods or services sold by the enterprise; PA1 Projections pertaining to the expected sales of the product or services in the market; PA1 Projections pertaining to the costs of producing products or rendering services (including the costs of materials, land, factories and equipment, or the cost of acquiring trained workers); PA1 Projections pertaining to factors of the general economy that would affect the marketing or making of the goods or services such as Gross National Product (GNP), cost of living, inflation, or unemployment rates; PA1 Projections pertaining to changes in the state of technology and the need for future research and development; PA1 Projections pertaining to the emerging product technology that will affect sales or evolution of a product; PA1 Projections pertaining to new products that will change the market or make the current products obsolete; and PA1 Projections pertaining to political or governmental influences on the making or marketing of the product, such as imposition of regulatory restrictions or taxes, or the political stability of a nation.
Projections provide the support for the resource allocation decisions. For a large industrial enterprise, creating projections based on these factors can be a substantial task, because projections for each factor will vary greatly, depending on the assumptions made and the problem solving approaches taken.
Generating the projections in strategic planning that are used as a basis for making resource allocation decisions is an inexact process. A key problem has been to develop a way to integrate the diverse and often conflicting information that is used in forming projections. Managers have access to a variety of incomplete, and often inconsistent information from many different sources, from which a complete and cohesive plan must be wrought. First, there is raw numerical data, concerning the enterprise itself and the products and/or services it provides. Budgets, sales figures, gross and net income figures, production totals, quantities of raw materials purchased, numbers of employees used, layoff figures, attrition rates, quantities concerning defective products, etc., are readily used for creating projections. As enterprises are generally careful in keeping records, the statistical information available on the enterprise is quite detailed and is available in varying levels of aggregation. In addition, there is also raw numerical information concerning the market for the product and the economy as a whole. Statistics such as market indicators, total market sales, demographic figures, as well as general economic factors such as GNP, inflation and unemployment rates are also readily available.
Along with this historical data, enterprises also promulgate general statements on their expectations for output and future sales that reflect either general corporate policy, expectation or the need for profit. Other information such as general knowledge of enterprise history, information on technology trends and information on governmental influences further affect projections. This additional information should be incorporated to make more realistic and persuasive projections.
To synthesize that raw statistical and other data and form projections, enterprise managers create models showing the relationships between the factors that will affect the projection, gather information on these factors, and then use different reasoning methods, such as causal modeling, correlational modeling, historical reasoning or input/output analysis, to make a projection. Each reasoning method for projection uses a different set of assumptions and performs its analysis on different data drawn from different factors. For any one projection needed in making a resource allocation decision, many different reasoning methods can be applied arriving at many different results. The results will differ, sometimes because of conflicting data used and sometimes because the assumptions and approaches implicit and explicit in each reasoning method vary. Managers may wish to perform "what if" analysis and create projections substituting different "made-up" values in the analysis, in a way similar to an engineer's use of system dynamics models. Further, the projection techniques can be applied to data at different levels of aggregation. Each of the projections created have differing levels of credibility or reliability, which the manager must evaluate in deciding which one to adopt.
Thus, much of the strategic planning activity involves understanding the significance of the numeric data, evaluating the assumptions of the reasoning methods used to transform that data into projections, measuring the credibility of the results, and then reconciling the various results by merging them or choosing between them.
For example, an enterprise manager may look at historic productivity trends to generate a projection about future productivity. Additionally, he or she may use knowledge of the causal forces that affect future productivity to generate an alternative projection. The "historical" and "causal" perspectives may suggest identical future productivity rates or they may differ sharply. In either case, they must be merged or reconciled. Merging and reconciling conflicting data relies heavily on the manager's knowledge of the credibility of the assumptions and data used to arrive at a result, the plausibility or reliability of each reasoning method, and how credible each reasoning method result appears in relation to the others. In any enterprise, different managers will have different views on how those factors should be applied, as it is always arguable that different factors should drive the process of determining strategy. Thus, in most enterprises, the strategic planning process involves multiple decision makers, each with various implicit and explicit goals. These goals are not reducible to one set of criteria. Thus, the decision-making process through reconciliation is highly subjective.
For many years, planners have sought the aid of computer-based tools in strategic planning. The problem has been to create a computer system to generate plausible recommendations concerning the nature and the amount of the various resources that are required to supply the enterprise, and identify the actions appropriate to acquire and develop these resources, given that there are a large number of factors to consider in planning and many different ways to consider them. The computer system must be able to analyze data from many different perspectives and form a single projection based on the results from the application of the different reasoning methods.
Commercial computer applications have played a minor role in the planning processes at this level. For instance, attempts at applying systems dynamics techniques to problems in strategic planning have several shortcomings. Because of its focus on the examination of the stability of the response to external stimuli and the feedback loops within its model of the enterprise, systems dynamics principles tend to over-emphasize the importance of transient behavior in the analysis of systems. More importantly, it ignores the context out of which starting parameters are derived and does not have any self-awareness, thus precluding explanation. It also lacks the ability to easily represent aggregate structures, and does not allow any consideration of alternate model structures within the one framework.
Also, other resource planning tools that are currently available employ an incomplete representation of the planning process. Such systems do not represent in any way the uncertainty associated with the forecast demand, nor do they allow for the consideration of change in the technology required to produce a product. The goals of the organization are not explicitly represented and problem solving as such is left entirely to the planner. Furthermore, these systems do not represent the context out of which planning parameters, such as productivity are derived. Alternate views are not represented. Neither systems any self-awareness of the methods it applies. Consequently such systems cannot offer any explanation of how planning parameters are derived or results generated.
As a result of these deficiencies, strategic planning in manufacturing is largely a manual process, with the primary computerized decision support coming from spreadsheet tools, word processing programs and electronic mail. There is considerable need for new modeling technology that can represent conflicting views and structures simultaneously within a system and which, in addition, has knowledge of the context out of which its parameters are derived and self-awareness of its reasoning processes so that reasoned explanations can always be generated to support the results that the system generates. Thus, the creation of a method and apparatus to adequately provide for the representation of all aspects of a system or entity, such as an enterprise, would be an advance and would have a wide range of uses in strategic planning and in other system analysis areas as well.